Description

Key Skills: Snowflake, Data architecture, AWS, Databricks

Roles and Responsibilities:

• Define conceptual, logical and physical data architectures for wealth management, investment reporting, portfolio accounting and analytics platforms.
• Design scalable ingestion, transformation and data availability patterns using AWS EMR, AWS Glue, AWS S3, Databricks and Amazon RDS.
• Translate business and technical requirements into high-level and low-level solution designs, data models and integration specifications.
• Establish data security, access control, governance and compliance patterns for enterprise data platforms.
• Provide architecture guidance to data engineers, review solution designs and code, and support estimation, sprint planning and release governance.

Skills Required:

• 15 - 19 years of experience in data architecture, cloud data platforms and enterprise data engineering.
• Extensive hands-on architecture experience with AWS EMR, AWS Glue and AWS S3.
• Strong Databricks experience across enterprise data engineering and lakehouse architecture.
• Experience designing data platforms and integrations using Amazon RDS and related cloud data services.
• Strong understanding of data modelling, SQL, data integration, security, scalability and enterprise data governance.

Good to Have:

• Experience with Databricks Unity Catalog, Snowflake, Power BI or Tableau, and data governance practices.
• Exposure to GenAI applications for data analytics and investment platforms or market data providers.

Education: Bachelor's or master's degree in computer science, information technology, engineering or a related discipline

Key Skills

Education

Any Graduate